CN114065339A - High tower construction site selection method based on three-dimensional visual model - Google Patents
High tower construction site selection method based on three-dimensional visual model Download PDFInfo
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Abstract
The invention discloses a high tower construction site selection method based on a three-dimensional visual model, which determines a target tower construction area according to a first node of a high tower and a last node of the high tower; generating three-dimensional image data corresponding to the target tower building area according to the two-dimensional image data acquired by the unmanned aerial vehicle; determining address information of a high tower preset node according to the landform parameters, the space parameters and the tower building standard information obtained from the three-dimensional image data; generating a high tower preset node distribution diagram in the three-dimensional image data corresponding to the target tower building area according to the address information, and connecting the high tower preset node distribution three-dimensional diagram, the high tower head node and the high tower tail node to obtain a line corridor three-dimensional model. The line corridor three-dimensional model can provide decision suggestions for users when the site selection of the high tower construction is carried out in the early construction stage. The method reduces the workload of outdoor surveying, reduces the labor cost and improves the working efficiency and the working quality.
Description
Technical Field
The invention relates to the field of high tower construction, in particular to a high tower construction site selection method based on a three-dimensional visual model.
Background
At present, in the early stage of construction and construction, a great deal of manpower and material resources are needed to carry out the early preparation work of the construction and construction, such as surveying the landform and the geomorphology and manually drawing related images. In the process of construction, the engineering personnel construct in sections according to the construction starting point and the construction finishing point required by the engineering, and select the next section of construction path or the next construction point while constructing. During the construction process, manual measurement, rechecking and construction point control are needed. Such a mode of operation is inefficient and the survey cycle is long. When the measurement and rechecking are carried out manually, due to the fact that errors exist in information acquisition, repeated unnecessary work can be carried out, and certain resource waste is brought.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a high tower construction site selection method based on a three-dimensional visual model, which can provide a reference position point and a reference construction path for high tower construction site selection based on a line corridor three-dimensional model in the early preparation work of high tower construction.
In a first aspect, an embodiment of the present invention provides a method for selecting a site for building a high tower based on a three-dimensional visualization model, including:
acquiring a high tower head node and a high tower tail node;
determining a target tower building area according to the high tower head node and the high tower tail node;
acquiring three-dimensional image data corresponding to the target tower building area, wherein the three-dimensional image data is generated according to two-dimensional image data acquired by an unmanned aerial vehicle;
obtaining a landform parameter and a space parameter according to the three-dimensional image data, wherein the landform parameter is used for representing landform characteristics, and the space parameter is used for describing longitude and latitude coordinates and altitude of any position point in the three-dimensional image data;
determining address information of a high tower preset node according to the landform parameters, the space parameters and the tower building standard information;
generating a high tower preset node distribution three-dimensional graph in the three-dimensional image data corresponding to the target tower building area according to the address information;
and connecting the high tower preset node distribution three-dimensional graph, the high tower head node and the high tower tail node to obtain a line corridor three-dimensional model, wherein the line corridor three-dimensional model is used for providing decision suggestions for users.
The technical scheme of the first aspect of the invention has at least one of the following advantages or beneficial effects: determining a first node and a last node of a high tower, and determining a target tower building area. And establishing a three-dimensional image corresponding to the target tower building area by utilizing the two-dimensional image data acquired by the unmanned aerial vehicle in the target tower building area. And obtaining related parameters through the three-dimensional image of the target tower building area, and determining the address information of the preset high tower node according to the related parameters and the tower building standard information. And marking the position of the preset nodes of the high tower on the three-dimensional image by the address information to obtain a three-dimensional graph of the distribution of the preset nodes of the high tower. And connecting the high tower preset node distribution three-dimensional graph, the high tower head node and the high tower tail node to obtain a line corridor three-dimensional model. The line corridor three-dimensional model shows all high tower nodes, high tower construction routes and route lengths between the high tower head node and the high tower tail node to a user, and the user can obtain address information of preset high tower nodes, a located site selection area and topographic parameters of a target tower construction area from the line corridor three-dimensional model. The line corridor three-dimensional model can provide decision suggestions for users when the high tower site selection is carried out in the early stage of construction, the workload of outdoor survey is reduced, certain labor cost is reduced, and the working efficiency and the working quality are improved; and in the later stage of engineering, when a surveying staff needs to carry out necessary on-site survey and measurement, reference data is provided for the surveying staff, the surveying range is selected, and the working efficiency of the engineering staff is improved.
According to some embodiments of the present invention, the acquiring three-dimensional image data corresponding to the target tower building area, where the three-dimensional image data is generated according to two-dimensional image data acquired by an unmanned aerial vehicle, includes:
acquiring two-dimensional image data acquired by the unmanned aerial vehicle in the target tower building area,
processing the two-dimensional image data to obtain normalized data, the two-dimensional image data including at least one of: engineering landform image data, local inclined image data, orthographic image data, laser point cloud data and multi-view image data;
establishing an engineering landform model and a digital elevation model based on the standardized data;
and according to the engineering landform model and the digital elevation model, utilizing three-dimensional modeling software to realize three-dimensional model reconstruction, and obtaining the three-dimensional image data corresponding to the target tower construction area.
According to some embodiments of the invention, the processing the two-dimensional image data to obtain normalized data comprises:
filtering the interference and noise in the two-dimensional image data according to an image filtering algorithm;
performing space-three encryption, geometric correction, geographic registration, cutting and splicing, coordinate conversion and slice issuing on the engineering landform image and the local inclined image data to obtain an engineering landform model;
processing the oblique image, the orthographic image data and the laser point cloud data according to image dense point cloud matching to obtain echo information in the laser point cloud data, wherein tree crown information and building edge information are reserved in the echo information, and the types of buildings and trees in the target tower building area are identified according to the echo information.
Processing the oblique image data, the orthographic image data and the laser point cloud data according to a stereo mapping technology, acquiring features of mountain terrain, water flow landform features, vegetation distribution features and road distribution features, and generating profile space three-dimensional result data by combining real-time space and ground distance;
matching the multi-view images by utilizing an SFM algorithm and an MVS algorithm to obtain sparse point cloud data and dense point cloud data of the target tower building area, and manufacturing an orthoimage of the target tower building area by using the vertical image;
and classifying the dense point cloud data by using a gridding mathematical morphology method and an iterative triangulation network interpolation method respectively to obtain ground point cloud data, wherein the ground point cloud data is used for generating a digital elevation model and a contour line.
According to some embodiments of the present invention, the determining address information of the high-tower preset node according to the topographic and geomorphic parameter, the spatial parameter and the tower construction specification information includes: and determining a target high tower construction position of a high tower preset node in the target tower construction area according to the topographic and geomorphic parameters, the space parameters and the tower construction specification information, wherein the address information comprises the space parameters of the target high tower construction position and the topographic and geomorphic parameters within a construction safety distance range.
According to some embodiments of the present invention, the determining a target high-tower construction position of a high-tower preset node in the target tower construction area according to the topographic and geomorphic parameter, the spatial parameter and the tower construction specification information includes:
carrying out multi-zone division on the target tower building area according to the landform parameters and the space parameters to obtain areas of different types;
determining an address selection area according to areas of different types and the tower construction specification information;
acquiring the area of the address selection area and a first safety distance threshold value between high tower nodes in the tower construction specification information;
and determining a high tower preset node and a target high tower construction position of the high tower preset node according to the area of the site selection area and the first safety distance threshold.
According to some embodiments of the invention, the topographical parameters comprise at least one of: a grade parameter; water flow landform characteristic parameters; house distribution characteristic parameters; and vegetation distribution parameters.
According to some embodiments of the present invention, the connecting the three-dimensional graph of the distribution of the preset nodes of the high tower, the head node of the high tower, and the tail node of the high tower to obtain the three-dimensional model of the line corridor includes:
marking the high tower head node and the high tower end node in the three-dimensional image data corresponding to the target tower building area;
acquiring address information of the high tower head node, the high tower end node and the high tower preset node;
according to the address information, carrying out road section test processing on the high tower head node, the high tower tail node and the high tower preset node to obtain a candidate road section;
determining a first path set taking the head node of the high tower as a starting point, a second path set taking the tail node of the high tower as a starting point and a third path set taking a preset node of the high tower as a starting point according to the candidate road sections;
combining and deleting candidate road sections in the first path set, the second path set and the third path set in sequence to obtain a total route set of all routes between the high tower head node and the high tower tail node;
acquiring the route lengths of all the routes in the general route set;
and performing model building and model connection processing on the high tower preset node distribution three-dimensional graph according to the total route set and the route length to obtain a line corridor three-dimensional model.
According to some embodiments of the present invention, according to the address information, a road segment test is performed on the high tower head node, the high tower end node, and the high tower preset node, so as to obtain a candidate road segment of the high tower head node, the high tower end node, and the high tower preset node; the method comprises the following steps:
combining the high tower head node, the high tower tail node and the high tower preset node into a high tower node set;
selecting a first high tower node according to the high tower node set, connecting the first high tower node with a second high tower node by taking the first high tower node as an initial point to obtain a test road section, and calculating a first distance of the test road section, wherein the second high tower node is other nodes of the high tower node set except the first high tower node;
determining that the test road segment is a candidate road segment of the first high tower node when the first distance is greater than a first safe distance threshold and less than a first loss distance threshold.
In a second aspect, an embodiment of the present invention further provides a server, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the control method of any one of the embodiments of the first aspect when executing the computer program.
In a third aspect, the embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, where the computer-executable instructions are configured to cause a computer to execute the control method according to any one of the embodiments of the first aspect.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flow chart of a method for selecting a site for building a high tower based on a three-dimensional visualization model according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to another embodiment of the present invention;
FIG. 3 is a schematic flow chart of a method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to another embodiment of the present invention;
FIG. 4 is a schematic flow chart of a method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to another embodiment of the present invention;
fig. 5 is a server according to an embodiment of the present invention.
Reference numerals: server 40, processor 41, memory 42.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
The embodiments of the present invention will be further explained with reference to the drawings.
The engineering project needs data construction. In the early stage of an engineering project, aiming at engineering requirements, an engineering power grid equipment model is established, wherein the engineering power grid equipment model comprises a single-loop linear tower, a double-loop linear tower and a corner tower which are constructed in a unified mode, a tension string, a jumper string and a suspension string which are constructed in a unified mode, and a substation electrical equipment, a building model and the like are constructed in a unified mode. After the manufacturing is completed, a relevant model result is formed: the system comprises a general engineering straight line tower model, a general engineering corner tower model, an insulator model, a construction equipment model, tower positioning parameters and a transformer substation model. The database models are general, and how to establish the engineering power grid equipment model database is not described herein.
For aerial images of the unmanned aerial vehicle, the images are obtained by continuously shooting by the same video camera, so that the focal length of the camera is known and is fixed; in the shooting process, relevant parameters at the shooting moment, including longitude and latitude, course, shooting height and shooting distance of a shooting place, are recorded by corresponding equipment.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for selecting a site for building a high tower based on a three-dimensional visualization model, which includes the steps of:
step S100, a high tower head node and a high tower tail node are obtained;
the determination and selection of the location of the high tower head node and the high tower end node is related to the implementation purpose of a specific engineering project. If power transmission is to be performed between two different locations, such as between villages, between cities, between villages and cities, the high tower head node and the high tower end node are selected according to engineering requirements, and the positions of the high tower head node and the high tower end node are not specifically limited in this application.
Step S110, determining a target tower building area according to a high tower head node and a high tower tail node;
the straight line of the route between the high tower head node and the high tower tail node is the shortest, but in practice, the high tower construction cannot be simply carried out according to the straight line due to the conditions of complex landforms, traffic distribution and the like. Therefore, a target tower building area needs to be selected, and the target tower building area also determines the aerial scope for carrying out aerial work of the unmanned aerial vehicle. The target tower building area cannot be too large, and if the target tower building area is too large, unmanned aerial vehicle resources are wasted; it is not too small, which is not good for finding the best construction path. The specific range needs to be determined according to construction specifications, engineering project requirements and project expenditure.
Step S120, three-dimensional image data corresponding to a target tower building area is obtained, and the three-dimensional image data is generated according to two-dimensional image data acquired by an unmanned aerial vehicle;
three-dimensional image data corresponding to the target tower building area can be obtained based on the two-dimensional image acquired by the unmanned aerial vehicle. The unmanned aerial vehicle can fly at ultra-low altitude and under the cloud for aerial photography, and cannot be shielded by the cloud layer to obtain images; and navigation and camera shooting control suitable for landform and ground objects can be realized, and ground scene images of multiple angles and multiple building surfaces are obtained to support construction of an urban three-dimensional landscape model. The unmanned aerial vehicle aerial image has the advantages of large scale, wide visual angle, high availability and the like.
Specifically, the drone used for mapping may have: an M210RTK unmanned aerial vehicle, a Phantom 4 RTK unmanned aerial vehicle, a longitude and latitude M210RTK V2 medium-sized aerial survey unmanned aerial vehicle and the like. The selection of unmanned aerial vehicle also can produce certain influence to the precision, does not do specific selection to the model of the unmanned aerial vehicle who uses in this application and does the restriction, as long as can gather the two-dimensional image data in the target tower construction region can.
Step S130, obtaining landform parameters and space parameters according to the three-dimensional image data, wherein the landform parameters are used for representing landform characteristics, and the space parameters are used for describing longitude and latitude coordinates and altitude of any position point in the three-dimensional image data.
Through unmanned aerial vehicle's collection, two-dimensional image carries two-dimensional coordinate position information. Based on the two-dimensional image, three-dimensional image data of the target tower building area can be obtained. The three-dimensional image reflects the landform of the target tower building area and the space coordinate parameters of any point on the three-dimensional image. The landform parameters and the space parameters can be intuitively read from the three-dimensional image data, and the user can directly acquire the desired data when viewing the three-dimensional image.
And step S140, determining the address information of the high tower preset node according to the landform parameters, the space parameters and the tower building standard information.
And determining a target high tower construction position of a high tower preset node in a target tower construction area according to the topographic and geomorphic parameters, the spatial parameters and the tower construction specification information, wherein the address information comprises the spatial parameters of the target high tower construction position and the topographic and geomorphic parameters within a construction safety distance range.
The landform parameters reflect the features of landforms, the spatial parameters determine the position of any point in the three-dimensional image, and the position suitable for building the high tower is found as the position of the preset node of the high tower by combining the tower building standard information and the limiting conditions of the geographic environment, so that the address information of the preset node of the high tower is further obtained. This step determines the appropriate location for the high tower to be constructed within the target tower-building area, which helps engineers to locate the site for the field survey faster if further field surveys are needed at a later time.
Step S150, generating a high tower preset node distribution three-dimensional graph in the three-dimensional image data corresponding to the target tower building area according to the address information;
and finding out points corresponding to the position information in the three-dimensional image according to the address information to serve as high-tower preset nodes, thereby forming a high-tower preset node distribution three-dimensional image.
And S160, connecting the high tower preset node distribution three-dimensional graph, the high tower head node and the high tower tail node to obtain a line corridor three-dimensional model, wherein the line corridor three-dimensional model is used for providing decision suggestions for a user.
And obtaining a three-dimensional graph of the distribution of the preset nodes of the high tower, determining the rough distribution of the construction site selection, and connecting the three-dimensional graph of the distribution of the preset nodes of the high tower, the first node of the high tower and the last node of the high tower to obtain a three-dimensional corridor model of the line. The connection processing here means that in the three-dimensional graph, connection is performed using a model in the engineering power grid equipment model database. The line corridor three-dimensional model shows all high tower nodes, construction lines and line lengths between the high tower head node and the high tower tail node for a user, decision suggestions can be provided for the user when high tower site selection is carried out in the early construction period, the workload of outdoor surveying is reduced, certain labor cost is reduced, and the working efficiency and the working quality are improved.
Referring to fig. 2, fig. 2 is a schematic flow chart of a high tower construction site selection method based on a three-dimensional visualization model according to another embodiment of the present invention, which is a detailed flow chart of step S120, and includes:
and S200, acquiring two-dimensional image data acquired by the unmanned aerial vehicle in a target tower building area.
After the unmanned aerial vehicle collects the two-dimensional image data, the data can be transmitted back to the server on the ground in real time through the high-power WiFi module.
Step S210, the two-dimensional image data is processed to obtain normalized data. The two-dimensional image data includes at least one of: engineering landform image data, local inclined image data, orthographic image data, laser point cloud data and multi-view image data;
and processing the original two-dimensional image data to obtain different types of standardized data. Based on standardized data, different high-precision digital models and engineering models can be established more quickly and efficiently in subsequent modeling work.
And S220, establishing an engineering landform model and a digital elevation model based on the standardized data.
The digital elevation model is a solid ground model which expresses the ground elevation in a group of ordered numerical value array forms, and other various terrain characteristic values can be derived from the digital elevation model. It is generally considered that the digital elevation model is a spatial distribution describing linear and nonlinear combination of various topographic factors including elevation, such as gradient, slope direction, gradient change rate and other factors, wherein the digital elevation model is a zeroth-order simple single-term digital topographic model, and other topographic characteristics such as gradient, slope direction and gradient change rate can be derived on the basis of the digital elevation model. The establishment of the digital elevation model is beneficial to quickly and conveniently acquiring some landform parameters subsequently.
And step S230, utilizing three-dimensional modeling software to realize three-dimensional model reconstruction according to the engineering terrain and landform model and the digital elevation model, and obtaining three-dimensional image data corresponding to the target tower building area.
The existing three-dimensional modeling software with mature application is utilized to realize the reconstruction of the three-dimensional model, and is more reliable and faster. Specifically, the current common software for three-dimensional reconstruction mainly includes: OpenGL, 3DS Max, Maya, and so on. No matter which software is used for constructing the three-dimensional image data, the three-dimensional image data can be constructed based on the obtained two-dimensional data information, and the selected three-dimensional reconstruction software is not particularly limited in the present application.
It can be understood that the range of single-lens shooting of the unmanned aerial vehicle is limited, and multiple continuous two-dimensional image data can be obtained from multiple angles and multiple shooting heights aiming at a target tower building area. Since the features of the ground features are different in different two-dimensional image data, some processing is required to be performed on the two-dimensional image data to make the two-dimensional image data standardized and usable in a unified manner. Based on this, step S210 will be further described specifically. Processing the two-dimensional image data to obtain normalized data, comprising:
filtering interference and noise in the two-dimensional image data according to an image filtering algorithm;
at actual environment relatively complicacy, unmanned aerial vehicle is gathering the in-process of two-dimensional image, inevitably can receive noise pollution or other interference, before handling two-dimensional image data, carries out filtering, can make the data that obtain more accurate, is favorable to establishing more accurate three-dimensional model. Specifically, the image filtering algorithm that can be used is: the method comprises the following steps of average filtering algorithm, wiener filtering algorithm, wavelet filtering algorithm and the like, and the adopted filtering algorithm is not limited as long as the image filtering can be realized.
Performing space-three encryption, geometric correction, geographic registration, cutting and splicing, coordinate conversion and slice issuing on the engineering landform image and local inclined image data to obtain an engineering landform model;
the space-three encryption is to analyze the space triangulation, and the ground coordinates and elevation data of the unknown points in the shot area are solved on a computer by taking the coordinates of the image points measured on the two-dimensional image as the basis, adopting a mathematical model and using a small number of field control points as constraint conditions according to the principle of the least square method.
Geometric correction can be applied through a series of mathematical models to correct and eliminate geometric distortion. When the remote sensing image is imaged, the characteristics of geometric positions, shapes, sizes, orientations and the like of all the objects on the original image are often inconsistent with the characteristics of the corresponding ground objects due to the comprehensive influence of various factors, and the inconsistency is geometric deformation. And after geometric correction, obtaining corrected image data which is closer to the actual features of the ground and ground objects. The geometric correction corrects a coordinate system aiming at one image, and is beneficial to forming a more accurate three-dimensional image.
The geographic registration is to register the control points as the positions of the reference points, so as to establish a one-to-one correspondence relationship between two coordinate systems in two-dimensional images. The geographic registration is mainly used before the map is digitized, and the map is corrected in coordinates and projection, so that map coordinate points are accurate, and the map is spliced accurately.
And the cutting and splicing are to process the data of a plurality of two-dimensional images based on the result of geographic registration to obtain a two-dimensional image with a larger coverage area.
And (4) carrying out coordinate conversion, and converting the two-dimensional coordinate system into a three-dimensional coordinate system. In general, since the time interval between continuously captured aerial images is short, it is approximate that an unmanned aerial vehicle captures images parallel to a certain point in the actual terrain, and a captured model is obtained based on a binocular stereoscopic vision model in which cameras are parallel in the lateral direction. According to the height information shot by the image, the altitude of the space point is rapidly solved, and then the three-dimensional coordinate information of the space point is obtained. For two continuously shot aerial images, under the condition that the image coordinate information of each characteristic point pair in the two images is known, the three-dimensional coordinate information of the characteristic points can be quickly and conveniently obtained.
And (4) issuing the slices, wherein the slices are projections of ground features relative to the ground, and the engineering landform and terrain model can be obtained by combining a plurality of layered slices.
Processing the oblique image data, the normal image data and the laser point cloud data according to the dense point cloud matching of the image to obtain echo information in the laser point cloud data, wherein tree crown information and building edge information are reserved in the echo information, and the types of buildings and trees in the target tower building area are identified according to the echo information.
The laser cloud data is obtained by a laser radar. The laser radar receives the returned laser beam, stores the laser foot points according to the time sequence and obtains the high-precision three-dimensional coordinates of the measured object. The laser radar has strong penetrating power, strong anti-interference capability and excellent detection performance. The laser beam can easily penetrate through the tree gap to obtain the position information of the bottom of the tree. Due to the shielding of leaves, branches and buildings, echo information is formed, and crown information of trees and edge information of buildings can be well reserved; the ground object has different absorption capacities to the laser beam, so that the intensity information of the echo received by the laser radar shows larger difference. The echo and the intensity information of the laser scanning point cloud can be used for detecting vegetation, roads, building edges and the like.
And performing dense matching point cloud elevation precision evaluation by taking the laser scanning point cloud as reference data. The laser scanning point cloud is segmented by region growing based on points, and a roof surface with stable position and geometric structure is extracted. Aiming at the condition of adhesion between a building and a tree, firstly, dividing point cloud based on dense matching point cloud color information and multi-scale point cloud normal line difference, establishing neighborhood voting by taking the distribution characteristics of tree points as a basis, and removing the tree points; extracting grid top points through the virtual grid tissue point cloud, segmenting a ground object structure with obvious top elevation difference by using the idea of region growth, and describing the maximum plane characteristics inside the segmented pattern spots by adopting plane bit characteristics; and finally, taking the building structure as prior knowledge, combining over-segmentation results, calculating a feature vector, inputting the feature vector into a support vector machine, and judging the category attribute of the vertical point according to the extraction result of the grid top point to obtain a complete building point set.
Processing the oblique image data, the orthographic image data and the laser point cloud data according to a three-dimensional mapping technology, acquiring the features of mountain terrain, water flow landform, vegetation distribution and road distribution, and generating profile space three-dimensional result data by combining real-time space and ground distance;
and matching the multi-view images by utilizing an SFM algorithm and an MVS algorithm to obtain sparse point cloud data and dense point cloud data of the target tower building area, and manufacturing an orthoimage of the target tower building area by using a vertical image.
The SFM (Structure from motion) algorithm is also called a motion inference structure algorithm, and can process a series of multiple views of the same object and scene to obtain a rough 3D shape of the scene, namely sparse point cloud data, and simultaneously obtain camera space parameters; MVS (Multi View Stereo), also called multi-View stereo algorithm, processes a series of multi-views of the same object and scene on the basis of camera parameters obtained by SFM algorithm, uses the MVS algorithm to refine the grids obtained by SFM technology, and carries out dense reconstruction to obtain dense point cloud data. MVS will typically take into account lighting and object material in the optimization process. The SFM performs 3D reconstruction using a structured image sequence, and the MVS is based on the reconstruction of dual view stereo vision, which is human stereo vision. And then combining the vertical image to make an orthoimage of the target tower building area.
And classifying the dense point cloud data by using a gridding mathematical morphology method and an iterative triangulation network interpolation method respectively to obtain ground point cloud data, wherein the ground point cloud data is used for generating a digital elevation model and a contour line.
Referring to fig. 3, fig. 3 is a schematic flow chart of a high tower construction site selection method based on a three-dimensional visualization model according to another embodiment of the present invention, which is a detailed flow chart of step S140. The method comprises the following steps:
and step S300, carrying out multi-zone division on the target tower building area according to the landform parameters and the space parameters to obtain areas of different types.
Specifically, the topographic parameters include at least one of: gradient parameters, water flow landform characteristic parameters, house distribution characteristic parameters and vegetation distribution parameters.
Dividing the target tower building area into a gentle terrain area, a steep terrain area and an impassable terrain area according to the gradient parameter and the gradient threshold; dividing a target tower building area into a water flow landform area and a non-water flow landform area according to the water flow landform characteristic parameters; dividing a target tower building area into a gathering area and a non-gathering area according to the house distribution characteristic parameters and the house distribution density threshold; dividing the target tower building area into a vegetation distribution area and a non-vegetation distribution area according to the vegetation distribution parameters and the plant distribution density threshold; and obtaining an addressing area according to the overlapped areas of the gentle terrain area, the non-water flow landform area, the non-gathering area and the non-vegetation distribution area.
It should be noted that the topographic parameters are not limited to the parameters mentioned in this application, and the topographic parameters may also include: slope direction, slope change rate, water collection area and the like. Different topographic and geomorphic parameters can be selected according to specific engineering construction requirements to divide the target tower construction area to obtain different types of areas.
Step S310, determining an address selection area according to areas of different types and tower construction standard information;
in the actual construction process, complex topography and landform can be encountered. In engineering construction, high tower buildings are generally constructed in a gentle terrain area, but not in an excessively steep terrain area. This ensures that large construction machines can enter the construction site; the construction site should be set in a non-water flow landform area, the geology of the water flow landform area is loose, the construction site is not suitable for building a foundation construction high tower, and the construction progress, the construction quality and the use of subsequent engineering buildings can be influenced by the water rise or flood discharge of rivers in rainy seasons; in consideration of the requirement for reducing construction influence, the site selection should be far away from the region where people gather such as villages and schools; in consideration of environmental protection, the vegetation is distributed far away from a place with dense vegetation as far as possible, and damage to the local ecological environment is reduced.
And determining areas which simultaneously meet a plurality of tower building standard conditions as site selection areas in the target tower building area based on the obtained areas of different types. The landform which does not conform to the site selection of engineering construction is screened out through the landform parameters, so that the site selection area is further reduced, and a foundation is laid for subsequent site selection work. When the field investigation is required, the method can provide reference for the survey staff when selecting the survey range, reduce the workload of the survey staff and provide convenience for the work of the survey staff.
Step S320, acquiring the area of the addressing area and a first safe distance threshold value between high tower nodes in the tower building standard information;
different high towers have different high tower interval specifications, and the safe distance threshold is selected according to the type of the high tower in the actual engineering construction.
Step S330, determining high tower preset nodes and target high tower construction position information of the high tower preset nodes according to the area of the site selection area and the first safety distance threshold.
And after the address selection area is obtained, calculating the area of the address selection area. In the tower building specification information, a certain safety distance is required between high tower nodes. A high tower node is taken as a circle center, the minimum safety distance is taken as a radius to make a circle, and a second high tower node cannot be selected within the circle range. The maximum number of high tower construction site selection points in one site selection area can be obtained by dividing the area of the site selection area by the area of the circle. In the address selection area, according to geographic terrain parameters of specific position points, such as parameters of slope direction, tangential curvature and the like, high tower preset nodes are determined, and address information of the high tower preset nodes is obtained at the same time.
Referring to fig. 4, fig. 4 is a schematic flow chart of a high tower construction site selection method based on a three-dimensional visualization model according to another embodiment of the present invention, and the step S160 is further refined, including:
step S400, marking a high tower head node and a high tower tail node in three-dimensional image data corresponding to a target tower building area;
step S410, acquiring address information of a high tower head node, a high tower tail node and a high tower preset node;
and acquiring address information of a high tower head node, a high tower tail node and a high tower preset node from the three-dimensional image data corresponding to the target tower building area.
And step S420, according to the address information, carrying out road section test processing on the first node of the high tower, the last node of the high tower and the preset node of the high tower to obtain a candidate road section.
In this step, specifically, a high tower head node, a high tower end node and a high tower preset node set are combined into a high tower node set; selecting a first high tower node according to the high tower node set, connecting the first high tower node with a second high tower node by taking the first high tower node as an initial point to obtain a test road section, and calculating a first distance of the test road section, wherein the second high tower node is other nodes of the high tower node set except the first high tower node; and under the condition that the first distance is greater than a first safety distance threshold and smaller than a first loss distance threshold, determining that the test road section is a candidate road section of the first high tower node.
If the distance between two high towers is too long, the electric power is greatly lost in the transmission process, so that the transmission cost of the electric power is too high, and the overlong transmission line is more easily affected by extreme weather. Therefore, the first loss distance threshold value is determined according to the high tower construction specification information, and the distance between two high towers cannot be larger than the first loss distance threshold value. And when the first distance of the test road section is greater than the first safety distance threshold and less than the first loss distance threshold, determining the test road section as a candidate road section of the first high tower node. Actual high tower construction specification information is referred to, so that the determined candidate road section has higher feasibility.
Step S430, according to the candidate road sections, determining a first path set taking a first node of the high tower as a starting point, a second path set taking a last node of the high tower as a starting point, and a third path set taking a preset node of the high tower as a starting point.
Step S440, combining and deleting candidate road sections in the first path set, the second path set and the third path set in sequence to obtain a total route set of all routes between a high tower head node and a high tower tail node;
and comparing the candidate road sections in the first path set, the second path set and the third path set, and deleting the candidate road sections from the second path set and the third path set when the first high tower node and the second high tower node of the two candidate road sections are consistent and the candidate road sections are repeated. Selecting a first candidate path from the first path set, and selecting a second candidate path from the third path set according to a second high tower node of the first candidate path for merging; and selecting a third candidate path from the second path set according to a second high tower node of the second candidate path for merging to obtain a high tower construction route comprising a high tower head node and a high tower tail node. And selecting a candidate path from the first path set to obtain all the paths between the high tower head node and the high tower tail node.
Step S450, acquiring the route lengths of all the routes in the general route set;
and step S460, performing model building and model connection processing on the high tower preset node distribution three-dimensional graph according to the total route set and the route length to obtain a line corridor three-dimensional model.
And (4) confirming the positions of the tower and transformer substation models by utilizing the engineering power grid equipment model database and combining with the construction route map, the tower detail table, the transformer substation floor layout map and other data. Various model data are combined with tower coordinate data and displayed in a three-dimensional scene to obtain a line corridor three-dimensional model, a user can obtain a high tower construction line and topographic parameters and space parameters around a high tower preset node through the model, all high tower nodes, construction lines and line lengths between a high tower head node and a high tower tail node can be observed visually, decision suggestions are provided for the user when high tower site selection is carried out in the early stage of construction, the workload of outdoor survey is reduced, the labor cost is reduced, and the working efficiency and the working quality are improved. When the on-the-spot survey needs exist in the later stage, the reference can be provided for the survey staff, and the work efficiency of the survey staff is improved.
Referring to fig. 5, a server 40 according to an embodiment of the second aspect of the present invention is provided. The server 40 includes but is not limited to: a memory 42 for storing programs; a processor 41 for executing the program stored in the memory 42. The processor 41 and the memory 42 may be connected by a bus or other means.
The memory 42, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. Processor 41 implements the above-described high tower construction site selection method by executing non-transitory software programs and instructions stored in memory 42.
The memory 42 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data for performing the above-described high tower addressing method. Further, the memory 42 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 42 optionally includes memory located remotely from the processor 41, and these remote memories may be connected to the processor 41 via a network.
The non-transitory software programs and instructions required to implement the above-described three-dimensional visualization model-based tower construction site selection method are stored in the memory 42 and, when executed by the one or more processors 41, perform the above-described tower construction site selection method, e.g., performing method steps S100 to S160 depicted in fig. 1, method steps S200 to S230 depicted in fig. 2, method steps S300 to S330 depicted in fig. 3, and method steps S400 to S460 depicted in fig. 4.
Additionally, an embodiment of the present invention also provides a computer-readable storage medium having stored thereon computer-executable instructions for execution by one or more control processors. The one or more control processors perform the three-dimensional visualization model-based high tower construction site selection method in the above method embodiment, for example, perform the above-described method steps S100 to S160 depicted in fig. 1, the method steps S200 to S230 depicted in fig. 2, the method steps S300 to S330 depicted in fig. 3, and the method steps S400 to S460 depicted in fig. 4.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods disclosed above may be implemented as software, firmware, hardware, or suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, CD-ROM, or any other medium which can be used to store the desired information and which can be accessed by the computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (10)
1. A high tower construction site selection method based on a three-dimensional visualization model is characterized by comprising the following steps:
acquiring a high tower head node and a high tower tail node;
determining a target tower building area according to the high tower head node and the high tower tail node;
acquiring three-dimensional image data corresponding to the target tower building area, wherein the three-dimensional image data is generated according to two-dimensional image data acquired by an unmanned aerial vehicle;
obtaining a landform parameter and a space parameter according to the three-dimensional image data, wherein the landform parameter is used for representing landform characteristics, and the space parameter is used for describing longitude and latitude coordinates and altitude of any position point in the three-dimensional image data;
determining address information of a high tower preset node according to the landform parameters, the space parameters and the tower building standard information;
generating a high tower preset node distribution three-dimensional graph in the three-dimensional image data corresponding to the target tower building area according to the address information;
and connecting the high tower preset node distribution three-dimensional graph, the high tower head node and the high tower tail node to obtain a line corridor three-dimensional model, wherein the line corridor three-dimensional model is used for providing decision suggestions for users.
2. The method for selecting a site for building a high tower based on a three-dimensional visualization model according to claim 1, wherein the obtaining of the three-dimensional image data corresponding to the target tower building area, the three-dimensional image data being generated according to the two-dimensional image data acquired by the unmanned aerial vehicle, comprises:
acquiring two-dimensional image data acquired by the unmanned aerial vehicle in the target tower building area,
processing the two-dimensional image data to obtain normalized data, the two-dimensional image data including at least one of: engineering landform image data, local inclined image data, orthographic image data, laser point cloud data, multi-view image data and vertical images;
establishing an engineering landform model and a digital elevation model based on the standardized data;
and according to the engineering landform model and the digital elevation model, utilizing three-dimensional modeling software to realize three-dimensional model reconstruction, and obtaining the three-dimensional image data corresponding to the target tower construction area.
3. The method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to claim 2, wherein the processing the two-dimensional image data to obtain standardized data comprises:
filtering the interference and noise in the two-dimensional image data according to an image filtering algorithm;
performing space-three encryption, geometric correction, geographic registration, cutting and splicing, coordinate conversion and slice issuing on the engineering landform image and the local inclined image data to obtain an engineering landform model;
processing the oblique image, the orthographic image data and the laser point cloud data according to image dense point cloud matching to obtain echo information in the laser point cloud data, wherein tree crown information and building edge information are reserved in the echo information, and the types of buildings and trees in the target tower building area are identified according to the echo information;
processing the oblique image data, the orthographic image data and the laser point cloud data according to a stereo mapping technology, acquiring features of mountain terrain, water flow landform features, vegetation distribution features and road distribution features, and generating profile space three-dimensional result data by combining real-time space and ground distance;
matching the multi-view images by utilizing an SFM algorithm and an MVS algorithm to obtain sparse point cloud data and dense point cloud data of the target tower building area, and manufacturing an orthoimage of the target tower building area by using the vertical image;
and classifying the dense point cloud data by using a gridding mathematical morphology method and an iterative triangulation network interpolation method respectively to obtain ground point cloud data, wherein the ground point cloud data is used for generating a digital elevation model and a contour line.
4. The method for selecting a site for building a high tower based on a three-dimensional visualization model according to claim 1, wherein the determining the address information of the preset nodes of the high tower according to the topographic parameters, the spatial parameters and the tower building specification information comprises:
and determining a target high tower construction position of a high tower preset node in the target tower construction area according to the topographic and geomorphic parameters, the space parameters and the tower construction specification information, wherein the address information comprises the space parameters of the target high tower construction position and the topographic and geomorphic parameters within a construction safety distance range.
5. The method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to claim 4, wherein the determining a target high tower construction position of a preset high tower node in the target tower construction area according to the topographic parameter, the spatial parameter and the tower construction specification information comprises:
carrying out multi-zone division on the target tower building area according to the landform parameters and the space parameters to obtain areas of different types;
determining an address selection area according to areas of different types and the tower construction specification information;
acquiring the area of the address selection area and a first safety distance threshold value between high tower nodes in the tower construction specification information;
and determining a high tower preset node and a target high tower construction position of the high tower preset node according to the area of the site selection area and the first safety distance threshold.
6. The method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to claim 5, wherein the topographic parameters comprise at least one of: a grade parameter; water flow landform characteristic parameters; house distribution characteristic parameters; and vegetation distribution parameters.
7. The method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to claim 1, wherein the step of connecting the three-dimensional graph of the distribution of the preset nodes of the high tower, the first node of the high tower and the last node of the high tower to obtain the three-dimensional model of the line corridor comprises the steps of:
marking the high tower head node and the high tower end node in the three-dimensional image data corresponding to the target tower building area;
acquiring address information of the high tower head node, the high tower end node and the high tower preset node;
according to the address information, carrying out road section test processing on the high tower head node, the high tower tail node and the high tower preset node to obtain a candidate road section;
determining a first path set taking the head node of the high tower as a starting point, a second path set taking the tail node of the high tower as a starting point and a third path set taking a preset node of the high tower as a starting point according to the candidate road sections;
combining and deleting candidate road sections in the first path set, the second path set and the third path set in sequence to obtain a total route set of all routes between the high tower head node and the high tower tail node;
acquiring the route lengths of all the routes in the general route set;
and performing model building and model connection processing on the high tower preset node distribution three-dimensional graph according to the total route set and the route length to obtain a line corridor three-dimensional model.
8. The method for selecting the address for the construction of the high tower based on the three-dimensional visualization model according to claim 7, wherein the method comprises the steps of performing a road segment test on the head node of the high tower, the end node of the high tower and the preset node of the high tower according to the address information to obtain a candidate road segment of the head node of the high tower, the end node of the high tower and the preset node of the high tower; the method comprises the following steps:
combining the high tower head node, the high tower tail node and the high tower preset node into a high tower node set;
selecting a first high tower node according to the high tower node set, connecting the first high tower node with a second high tower node by taking the first high tower node as an initial point to obtain a test road section, and calculating a first distance of the test road section, wherein the second high tower node is other nodes of the high tower node set except the first high tower node;
determining that the test road segment is a candidate road segment of the first high tower node when the first distance is greater than a first safe distance threshold and less than a first loss distance threshold.
9. A server, comprising: memory, processor and computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the method for addressing high tower construction based on three-dimensional visualization models according to any of claims 1 to 8.
10. A computer-readable storage medium storing computer-executable instructions, wherein the computer is capable of executing the method for selecting a site for constructing a high tower based on a three-dimensional visualization model according to any one of claims 1 to 8.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114863275A (en) * | 2022-04-27 | 2022-08-05 | 北京良安科技有限公司 | Three-dimensional mapping method, system, equipment and storage medium for granary |
| CN115115221A (en) * | 2022-06-25 | 2022-09-27 | 国网安徽省电力有限公司经济技术研究院 | Narrow-base steel tower construction analysis method based on cloud computing |
| CN115796557A (en) * | 2023-02-02 | 2023-03-14 | 湖北君邦环境技术有限责任公司 | Method, system and medium for evaluating ecological influence of power transmission and transformation project construction project |
| CN115796329A (en) * | 2022-10-25 | 2023-03-14 | 厦门亿力吉奥信息科技有限公司 | Power grid planning system based on geographic information |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114863275A (en) * | 2022-04-27 | 2022-08-05 | 北京良安科技有限公司 | Three-dimensional mapping method, system, equipment and storage medium for granary |
| CN115115221A (en) * | 2022-06-25 | 2022-09-27 | 国网安徽省电力有限公司经济技术研究院 | Narrow-base steel tower construction analysis method based on cloud computing |
| CN115115221B (en) * | 2022-06-25 | 2023-08-08 | 国网安徽省电力有限公司经济技术研究院 | Narrow-base steel tower construction analysis method based on cloud computing |
| CN115796329A (en) * | 2022-10-25 | 2023-03-14 | 厦门亿力吉奥信息科技有限公司 | Power grid planning system based on geographic information |
| CN115796329B (en) * | 2022-10-25 | 2024-06-11 | 厦门亿力吉奥信息科技有限公司 | Power grid planning system based on geographic information |
| CN115796557A (en) * | 2023-02-02 | 2023-03-14 | 湖北君邦环境技术有限责任公司 | Method, system and medium for evaluating ecological influence of power transmission and transformation project construction project |
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